Pregled bibliografske jedinice broj: 1189634
Classification of asthma using artificial neural network
Classification of asthma using artificial neural network // Proceedings of 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) 2016 / Biljanović, Petar (ur.).
Rijeka: Institute of Electrical and Electronics Engineers (IEEE), 2016. str. 387-390 doi:10.1109/mipro.2016.7522173 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1189634 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Classification of asthma using artificial neural
network
Autori
Badnjevic, Almir ; Gurbeta, Lejla ; Cifrek, Mario ; Marjanovic, Damir
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) 2016
/ Biljanović, Petar - Rijeka : Institute of Electrical and Electronics Engineers (IEEE), 2016, 387-390
ISBN
978-953-233-087-8
Skup
39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) 2016
Mjesto i datum
Opatija, Hrvatska, 30.05.2016. - 03.06.2016
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
asthma ; classification ; artificial neural networks
Sažetak
This paper presents a system for classification of asthma based on artificial neural network. A total of 1800 Medical Reports were used for neural network training. The system was subsequently tested through the use of 1250 Medical Reports established by physicians from hospital Sarajevo. Out of the aforementioned Medical Reports, 728 were diagnoses of asthma, while 522 were healthy subjects. Out of the 728 asthmatics, 97.11% were correctly classified, and the healthy subjects were classified with an accuracy of 98.85%. Sensitivity and specificity were assessed, as well, which were 97.11% and 98.85%, respectively. Our system for classification of asthma is based on a combination of spirometry (SPIR) and Impulse Oscillometry System (IOS) test results, whose measurement results were inputs to artificial neural network. Artificial neural network is implemented to obtain both static and dynamic assessment of the patient's respiratory system.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Kliničke medicinske znanosti
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
